Operational management of the cane infield wagon: Analysis of the cost of repair and maintenance

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1 ISSN Revista Brasileira de Egeharia Agrícola e Ambietal v.22,.3, p , 2018 Campia Grade, PB, UAEA/UFCG DOI: Operatioal maagemet of the cae ifield wago: Aalysis of the cost of repair ad maiteace Cezario Galvão 1, Agel P. Garcia 1, Daeil Albiero 2, Admilso Í. Ribeiro 3 & Âgelo D. Bachi 4 1 Uiversidade Estadual de Campias/Faculdade de Egeharia Agrícola. Campias, SP. cezario.galvao@feagri.uicamp.br - ORCID: (Correspodig author); agel.garcia@feagri.uicamp.br - ORCID: Uiversidade Federal do Ceará. Fortaleza, CE. daiel.albiero@gmail.com - ORCID: Uiversidade Estadual Paulista Júlio de Mesquita Filho/Campus Experimetal de Sorocaba. Sorocaba, SP. admilso@sorocaba.uesp.br - ORCID: ASSISTE Egeharia de Softwares. Piracicaba, SP. agelo@assiste.com.br - ORCID: Key words: mechaical harvestig of sugarcae maagemet of mechaizatio agricultural costs A B S T R A C T I the mechaical harvestig of sugarcae, a self-propelled harvester is used i cojuctio with a agricultural implemet amed ifield wago, which has the fuctio of storig ad trasportig the harvested product. Much of the cost of sugarcae productio comes from this operatio (30 to 60%). Amog the operatioal costs of agricultural machiery, the cost of repair ad maiteace (CRM) is relevat. Therefore, the objective of this study was to determie the parameters of the CRM mathematical model based o the life (hours of use) for the ifield wago, usig the method of the America Society of Agricultural ad Biological Egieers (ASABE). These CRM models were obtaied for two sets of ifield wago from differet maufacturers ad their costs over up to 12 years. The model was adjusted ad the validated usig descriptive statistics methods. Fitted CRM equatios were differet for each aalyzed set of ifield wago ad, therefore, are a valuable tool i the maagemet of mechaizatio i sugarcae mills as it provides elemets that ca support decisio-makig of maagers i the acquisitio ad maagemet of agricultural implemets. Palavras-chave: colheita mecaizada da caa-deaçúcar gestão da mecaização custos agrícolas Gestão operacioal do trasbordo de caa-de-açúcar: Aálise do custo de reparo e mauteção R E S U M O Na colheita mecaizada de caa-de-açúcar é utilizada uma colhedora autopropelida em cojuto com uma máquia agrícola deomiada de trasbordo, que tem a fução de trasportar o produto colhido. Os custos com o corte, carregameto e trasporte variam etre 30 e 60% dos custos de produção da caa-de-açúcar. Detre os custos operacioais de máquias agrícolas, o custo de reparo e mauteção (CRM) possui relevâcia, sedo assim, objetivou-se este trabalho determiar os parâmetros do modelo matemático do CRM em fução da vida (horas de uso) para o trasbordo, utilizado o método da America Society of Agricultural ad Biological Egieers (ASABE). Estes modelos de CRM foram obtidos para dois cojutos de trasbordos de fabricates diferetes e seus dados despedidos ao logo de até 12 aos. O modelo foi ajustado e posteriormete validado utilizado métodos de estatística descritiva. As equações ajustadas do CRM foram diferetes para cada cojuto de trasbordo aalisado, sedo portato, uma ferrameta importate a gestão da mecaização as usias pois forece elemetos que podem subsidiar as tomadas de decisão dos gestores a aquisição e gereciameto de equipametos agrícolas. Ref Received 15 May, 2017 Accepted 20 Oct, 2017 Published 31 Ja, 2018

2 Operatioal maagemet of the cae ifield wago: Aalysis of the cost of repair ad maiteace 219 Itroductio Self-propelled harvesters are ot equipped with a tak that allows to store the sugarcae harvested; thus, they require a site to uload the product as they harvest. A agricultural vehicle, called ifield wago, has bee developed for this purpose. It stores harvested sugarcae ad takes it to the road trasport, outside the crop area. These machies prevet road vehicles from travelig iside platig areas, miimizig damages caused by soil compactio (Severiao et al., 2010; Pacheco & Catalice, 2011; Araújo et al., 2013). Satos et al. (2014) poit out that the machies used i the mechaized harvestig system i sugarcae mills are cosidered as the most expesive amog agricultural harvestig machies. Machiery costs are divided ito costs of property (fixed) ad operatioal or variable costs (Miette et al., 2008; Piacetii et al., 2012). The cost of repair ad maiteace (CRM) is a operatioal cost difficult to quatify, because its data are dispersed i various sectors of the same agricultural compay. A mathematical model that relates CRM to a machie s life has bee proposed by the America Society of Agricultural ad Biological Egieers (ASABE, 2003). This model presets a method i which accumulated CRM () is used as a fuctio of the machie s life. Parametrizatios for this model, for various types of agricultural machiery, are preseted i ASABE (2011). Noetheless, parameters relative to sugarcae ifield wago are ot preseted. Sice agricultural mechaizatio has a cotiuous flow of developmet ad creatio of ew techologies (Mercate et al., 2010), studies o the maagemet of these machies are ecessary. Baio et al. (2013) discuss the lack of iformatio o costs for machiery used i Brazil. Studies o CRM are importat to support the decisio-makig of compaies maagers (Silveira et al., 2006). Maagemet of fleets of machies has become icreasigly preset i the plaig of agricultural operatios, because a larger volume of data is collected by the productio sector (Sichoay et al., 2012). This study aimed to fit a mathematical model to calculate the, as proposed by ASABE, for agricultural ifield wagos, as a fuctio of life (hours of use) ad verify its applicatio for groups of vehicles i the same category. Material ad Methods Data were collected i a agricultural compay located i the regio of Ribeirão Preto- SP, Brazil (-21 o 10 S; -47 o 48 W), which delivers i its processig uit, o average, 4 to 5 thousad tos of sugarcae per day. Data composig the CRM were collected by a computerized fleet cotrol system (SISMA, of the Assiste Egeharia de Softwares Técicos). These pieces of iformatio were geerated by various sectors of the sugarcae mill ad the data of each vehicle were stored i databases. This study used data from 11 ifield wagos of the fleet of a mill, from two differet maufacturers, 4 vehicles of brad A, year of maufacture 200 which started operatig i the 2002 seaso, with 12 years of observatio, ad 7 vehicles of brad B, year of maufacture 2005, which started operatig i the 2005 seaso, with 9 years of observatio. The models have 8-to load capacity, two axles ad equal hydraulic lift system for uloadig, ad thus are characterized as similar. CRM calculatios, used to parametrize the model proposed by ASABE, followed the method proposed by Bachi et al. (2008), composed by various types of costs, as described i Eq. The terms i the equatio are give i Reais (R$) per uit of time. I the moths of calculatio of these costs, apportiomets refer to parts ad labor that caot be directly allocated to oe vehicle. CRM = CPC+ CLC + COP+ COL + AP + AL + CT where: CPC - costs with parts from the compay s stock; CLC - costs with labor of mechaics from the compay; COP - expases with outsourced parts, purchased from other compay; COL - costs with outsourced labor, mechaics of other compay; AP - apportiomet of parts; AL - apportiomet of labor; ad, CT - costs with tires. Sice these values are cosidered over time, moetary correctio becomes ecessary. The correctio idex used was the Exteded Natioal Cosumer Price Idex (IPCA), cosidered as the official iflatio rate i the coutry. Mothly accumulated data for each vehicle were updated ad summed for each ed of year, expressig the aual accumulatio, which is CRM. These aual costs were updated for a referece date. Therefore, values were moetarily corrected ad with the same referece date, so the sum of the aual values is defied as accumulated cost of repair ad maiteace (). The ifield wago s life was quatified i hours of use ad its mea time of use per year was calculated based o the mea of hours show by the tractors with which it worked. Hece, a value of 850 h of use year -1 was foud for each ifield wago. The method used to relate to a machie s life was proposed by ASABE, which calculates as a fuctio of the price of acquisitio of the ifield wago (PAC), corrected by the iflatio, of the accumulated use i hours () ad of two specific parameters for each type of machie, RF1 ad RF2, for a life (), accordig to Eq. 2. This procedure has bee detailed by Kastes (1997). RF = RF1PAC ( 10 3 ) 2 As ca be see i the equatio proposed by ASABE ad i the study of Wahby & Suhaibai (2001), the model with best fit is the expoetial. These authors demostrated that, whe the machies are separated by a certai characteristic, the regressios show a better correlatio betwee the data, compared with the database without groupig. Sice the expoetial fuctio was used, a base-10 log trasformatio was carried out i both data sets of accumulated cost of repair ad maiteace ( PAC -1 ), by the accumulated use of the machie (AR 10-3 ), Eq. 3. With (1) (2) R. Bras. Eg. Agríc. Ambietal, v.22,.3, p , 2018.

3 220 Cezário Galvão et al. these trasformed data, a liear regressio was performed to fid the parameters of the model, Eq. 4. Log( PAC 1 3 ) = alog( AR 10 ) + b Applyig atilog i the equatio leads to: where: RF1-10 b ; ad, RF2 - a. PAC = RF1( AR 10 ) 1 3 RF 2 To fit the model accordig to the method of ASABE, it was ecessary to obtai the values paid to purchase the vehicles: R$ 47,0000 for the oe of brad A, year of maufacture 200 ad R$ 63,0000 for the oe of brad B, year of maufacture These values were obtaied at the agricultural compay ad, whe corrected by the IPCA, demostrate equality, reiforcig the similarity betwee machies of differet brads. Parametrizatio ad fits of the models were validated usig the ANOVA Table, showig the F test, graph of residuals, coefficiet of correlatio R, ad the coefficiet of determiatio R 2, to aalyze the model to be adopted (software R). (3) (4) liear regressio equatios ad coefficiets of determiatio (R 2 ). Data of the brad-a vehicles (Figure 1A) showed correlatio coefficiet r = 973, whereas brad-b vehicles (Figure 1B) showed correlatio coefficiet r = 949, which idicates a liear associatio betwee the data. The residuals obtaied from the regressio curves were the aalyzed. Errors are idepedet ad ormally distributed, Figures 2A ad B, with o bias. Therefore, the model ca be cosidered as valid. Aalysis of variace (Table 1) was coducted with the ull hypothesis of rejectig H0: p-value = If the calculated p-value is differet from zero, the H0 hypothesis is rejected. Therefore, the regressio is sigificat. Accordig to the preseted model, the determiatio coefficiet, R 2, was equal to 94.68% for brad-a vehicles ad to 916% for brad-b vehicles. Based o the coefficiets, the model was adequate. The data obtaied by the liear regressios were used to make the ecessary trasformatios, show i Eq. 4, to fid the parameters of the models for brad-a vehicles, Eq. 5, ad brad-b vehicles, Eq. 6. Residual Results ad Discussio Figures 1A ad B preset the curves of correlatio betwee PAC -1 values after applyig base-10 logarithm, Residual Observatios Figure Scatter plot for the ifield wagos: (A) brad A; (B) brad B Observatios Figure 2. Graph of residuals of the regressios for brad-a (A) ad brad-b (B) vehicles R. Bras. Eg. Agríc. Ambietal, v.22,.3, p , 2018.

4 Operatioal maagemet of the cae ifield wago: Aalysis of the cost of repair ad maiteace 221 Table ANOVA for brad-a (A) ad brad-b (B) vehicles Source Degrees Quadratic Quadratic of variatio of freedom sum mea F 0 p-value Regressio e-16 Error Regressio e-16 Error = PAC 006 = PAC The same procedure was used for the etire set of poits, fidig Eq. 7, which is the geeral model of both types of vehicle. Figure 3 shows the graph with the three equatios. = PAC It ca be observed i Eqs. 5, 6 ad 7 that the parameters are affected by the brad of the vehicles. The factor RF1 varies from 006 to 015 ad the factor RF2 varies from 860 to 57 which sigificatly affects value, idicatig that, alog the life, the accumulated cost of repair ad maiteace will be higher for brad-a vehicles. A simulatio was carried out for three values of life: iitial, with 850 h; itermediate, with 9,250 h ad fial, with 16,650 h. Accordig to the PAC -1 values, for both brads studied, there were differeces of costs i the iitial poit of 115%, i the itermediate poit of 35% ad i the fial poit of 14%, ad brad-b vehicles always showed lower PAC -1 values compared with brad Sice the vehicles are similar i terms of load capacity, umber of axles, uload system with hydraulic lift ad prices of acquisitio (PAC), it ca be iferred that the materials composig the vehicles have differet quality or that a alteratio i the maufacturig process leads to a decrease i the resistace of some compoet. Such iformatio is importat i machiery maagemet, sice there are may maufacturers i the market, ad ca be relevat i the choice of the ext acquisitios of ifield wagos. The stadard error of each set of values (Table 2) was obtaied by usig the stadard error of the estimates of the Figure 3. obtaied through Eqs. 5, 6 ad 7, for the models A, B ad geeral, respectively (5) (6) (7) Table 2. Stadard error of the estimate for the geeral model (Eq. 7) ad the specific model of each brad Geeral model (Eq. 7) Specific model (Eqs. 5 ad 6) Brad A Brad B brads, which allows to measure the mea deviatio betwee actual values ad values estimated by the model, the actual values for each brad applied i Eq. 7 ad applied i the specific equatios of each brad, Eqs. 5 ad 6. It ca be oted that, as the data of the vehicles were grouped by brad, a better fit of the models was obtaied, because the stadard errors are lower tha the calculated oes for the model geerated by all poits, which is cosistet with the results preseted by Wahby & Suhaibai (2001). These authors cocluded that groupig machiery by homogeeous category (brad) teds to provide better fitted models. The preset study demostrates that there is a variatio of behavior amog the models of machies, a fact ot distiguished by ASABE, which shows geeral values for a rage of machies ad does ot cosider the differeces betwee models ad brads, as evideced i the publicatio table of ASABE (2011). Coclusios There is a correlatio betwee CRM ad ifield wago s life, ad it is possible to fit a mathematical model, as described by ASABE, for the ifield wago. 2. This method of data aalysis may assist i machiery maagemet, sice machies that are similar, but from differet brads, exhibit differet costs of repair. 3. Specific mathematical models for groups of machies, with similar characteristics, lead to more cosistet results compared with geeral mathematical models. Ackowledgmets To the Coordiatio for the Improvemet of Higher Educatio Persoel (CAPES) for the scholarship ad to the ASSISTE Egeharia de Softwares Técicos for providig the data ad iformatio about the SISM Literature Cited Araújo, F. S.; Souza, Z. M. de; Souza, G. S. de; Matsura, E. E.; Barbosa, R. S. Espacialização do itervalo hídrico ótimo de um Latossolo Vermelho em dois sistemas de colheita de caa-deaçúcar. Pesquisa Agropecuária Brasileira, v.48 p doi: 11590/S X org/11590/s x ASABE - America Society of Agricultural ad Biological Egieers. Agricultural machiery maagemet data. I: ASABE stadards D St. Joseph: ASABE, p. ASABE - America Society of Agricultural ad Biological Egieers. Agricultural machiery maagemet data. I: ASABE stadards D St. Joseph: ASABE, 201 6p. R. Bras. Eg. Agríc. Ambietal, v.22,.3, p , 2018.

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